“Unlearning” in AI: The New Frontier Challenging Data Privacy Norms and Reshaping Security Protocols

"In-Context Unlearning" removes specific information from the training set without the computational overhead. Traditional unlearning methods involve accessing and updating model parameters and are computationally taxing. In cases where models inadvertently learn sensitive information, unlearning can help remove this knowledge. While unlearning aims to enhance data privacy, its primary focus is on internal data management.

Read All

ai ai-trends cases computational context data data privacy future-of-ai generative-ai information knowledge learn llms machine-unlearning parameters privacy security set training unconscious-ai-bias unlearning